Model comparison
Kimi K2.5 vs Qwen2.5-VL 72B Instruct
Kimi K2.5 is the stronger model overall, scoring 48.1 to 29.9 on the Noometry Index.
Last verified . 3 shared benchmarks.
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. Kimi K2.5 scores higher in 3 categories and Qwen2.5-VL 72B Instruct in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Kimi K2.5 leads 34.2 to 18.6.
- The biggest single-benchmark swing is OSWorld: 63.3% for Kimi K2.5 and 5% for Qwen2.5-VL 72B Instruct.
- Kimi K2.5 is cheaper at $0.45 / $2.25 per million input/output tokens, against $2.80 / $8.40 for Qwen2.5-VL 72B Instruct.
- Kimi K2.5 accepts more context: 262K tokens versus 131K.
Side by side
| Kimi K2.5 | Qwen2.5-VL 72B Instruct | |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 48.1 | 29.9 |
| Released | 2026-01-27 | 2024-09 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 262K | 8K |
| Input $ / M tokens | $0.45 | $2.80 |
| Output $ / M tokens | $2.25 | $8.40 |
| Results tracked | 51 | 6 |
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Category by category
Coding Not comparable
Kimi K2.5: 48.8 (#53), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K2.5 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| SWE-bench Verified | 73.8% | — |
| SWE-bench Verified (bash only) | 70.8% | — |
| LMArena WebDev | 1437 | — |
| SWE-bench Multilingual | 67.3% | — |
| SciCode | 49% | — |
| WeirdML | 45.6% | — |
| LMArena Coding | 1474 | — |
| ALE-Bench | 821.65 | — |
Agentic & Tool Use Kimi K2.5 leads
Kimi K2.5: 34.2 (#48), Qwen2.5-VL 72B Instruct: 18.6 (#144)
| Benchmark | Kimi K2.5 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| OSWorld | 63.3% | 5% |
| Terminal-Bench | 43.2% | — |
| Vending-Bench 2 | 1,198 | — |
Reasoning Kimi K2.5 leads
Kimi K2.5: 31.2 (#80), Qwen2.5-VL 72B Instruct: 20.7 (#233)
| Benchmark | Kimi K2.5 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 78.5% | 36% |
| ARC-AGI-2 | 11.8% | — |
| SimpleBench | 46.8% | — |
| NYT Connections (extended) | 69.9% | — |
| ARC-AGI-1 | 65.3% | — |
| CritPt | 3.1% | — |
| Chess Puzzles | 12% | — |
| EnigmaEval | 3.4% | — |
| Thematic Generalization | 69.4% | — |
| LMArena Hard Prompts | 1453 | — |
| Epoch Capabilities Index | 148.03 | — |
Math Not comparable
Kimi K2.5: 51.8 (#53), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K2.5 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| MathArena Final-Answer Competitions | 62.3% | — |
| OTIS Mock AIME 2024-2025 | 92.2% | — |
| LMArena Math | 1470 | — |
| FrontierMath (Feb 2025 set) | 27.9% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Not comparable
Kimi K2.5: 53.6 (#56), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K2.5 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| GPQA Diamond | 87.6% | — |
| Humanity's Last Exam | 24.4% | — |
| SimpleQA Verified | 34.3% | — |
| Vectara Hallucination Rate | 14.2% | — |
| LMArena Expert | 1466 | — |
Multimodal Kimi K2.5 leads
Kimi K2.5: 41.1 (#39), Qwen2.5-VL 72B Instruct: 33.5 (#97)
| Benchmark | Kimi K2.5 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Vision | 1269 | 1107 |
| Video-MME | — | 73.5% |
| GeoBench | — | 62% |
| LMArena Document | 1430 | — |
| SpatialViz-Bench | — | 33.3% |
Multilingual Not comparable
Kimi K2.5: 53.9 (#53), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K2.5 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Non-English | 1433 | — |
| LMArena Chinese | 1495 | — |
| LMArena French | 1454 | — |
| LMArena German | 1441 | — |
| LMArena Japanese | 1421 | — |
| LMArena Korean | 1410 | — |
| LMArena Russian | 1435 | — |
| LMArena Spanish | 1450 | — |
Instruction Following Not comparable
Kimi K2.5: 75.3 (#64), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K2.5 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Instruction Following | 1431 | — |
Long Context Not comparable
Kimi K2.5: 52.1 (#7), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K2.5 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Fiction.LiveBench | 86.1% | — |
| CL-bench | 19.3% | — |
| CL-bench Life | 13.2% | — |
| LMArena Longer Query | 1445 | — |
Writing & Preference Not comparable
Kimi K2.5: 65.1 (#53), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K2.5 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Text | 1445 | — |
| LMArena Creative Writing | 1423 | — |
| EQ-Bench Creative Writing | 1579 | — |
| LMArena Multi-Turn | 1444 | — |
Frequently asked questions
Is Kimi K2.5 better than Qwen2.5-VL 72B Instruct?
Kimi K2.5 is the stronger model overall, scoring 48.1 to 29.9 on the Noometry Index.
Which is cheaper, Kimi K2.5 or Qwen2.5-VL 72B Instruct?
Kimi K2.5 is cheaper. It lists at $0.45 per million input tokens and $2.25 per million output tokens; Qwen2.5-VL 72B Instruct lists at $2.80 and $8.40.
Which has the bigger context window?
Kimi K2.5 does, with 262K tokens against 131K.
How many benchmarks do Kimi K2.5 and Qwen2.5-VL 72B Instruct share?
3 benchmarks have published results for both models. Kimi K2.5 has 51 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.